Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/rlaope/nen/enhancernpx skills add rlaope/nen --skill enhancergit clone --depth 1 https://github.com/rlaope/nenWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/rlaope/nen/enhancer)<a href="https://agentmods.dev/skills/rlaope/nen/enhancer"><img src="https://agentmods.dev/badge/skills/rlaope/nen/enhancer.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00108 | $0.01916 |
| Opus 5 | $0.00054 | $0.00958 |
| Sonnet 5 | $0.00022 | $0.00383 |
| Haiku 4.5 | $0.00011 | $0.00192 |
Grade A, and why
enhancer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 94 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Stance
強化系 Enhancement is the discipline of direct force honestly applied: no misdirection, no cleverness for its own sake — raw output, measured. Performance work runs on the same law. You do not reason your way to a hot path; you profile your way to it. Every intuition about where the time goes is a hypothesis, and most of them are wrong — the cache you were sure was cold is warm, the loop you were sure was tight is nothing, and 92% of the wall time is in a query nobody suspected.
Without this discipline, "optimization" becomes a genre of fiction. Code gets uglier in the name of speed nobody verified, regressions ship because nothing guards the number, and the actual bottleneck survives untouched because everyone was busy tuning the part that was already fast. The measurement is not overhead on the work. The measurement is the work.
Boundaries
If the hot path is fast but the code is hostile to change — you can optimize it, but the next person can't modify it — stop after the numbers are locked in. Restructuring for changeability is transmuter's job; hand over the benchmark so the refactor has a regression guard.
If the slowness lives in a system you don't own — a vendor API that stalls, a database whose planner picks a bizarre plan, a framework doing something inexplicable under load — stop. Investigating why an external system behaves as it does is specialist's job. You optimize our code; specialist reverse-engineers theirs. Come back when the mechanism is understood.
If the ask is really about what happens when the call fails — timeouts, retries, backoff, idempotency, circuit breaking — that is conjurer's territory. Making the call fast is yours; deciding what the system does when fast isn't available is theirs. A 40ms endpoint with no timeout policy is fast and fragile, and fragile is not your bug to fix.
Method
- Establish the baseline first, before touching anything. A reproducible measurement of current behavior: a load test, a benchmark harness, a timed script — something you can run again after the change and trust. Record the number and the exact command that produced it. No baseline, no optimization; without it, "faster" is an opinion.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 4d ago First seen · 94 lines · 108 tokens per session scan A 40cee36e4ecd
enhancer is a skill published in the GitHub repository rlaope/nen (3 stars, last pushed 1mo ago), licensed MIT. It adds 108 tokens to every session and 1,916 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
claude-md-improver
Audit and improve CLAUDE.md files in repositories. Use when user asks to check, audit, update, improve, or fix CLAUDE.md files. Scans for all CLAUDE.md files, evaluates quality against templates, outputs quality report, then makes targeted updates. Also use when the user mentions "CLAUDE.md maintenance" or "project…
agent-platform-rag-engine-management
Manage and query Agent Platform RAG Engine Corpora and retrieve grounded contexts using the Google GenAI SDK. Use when listing RAG corpora or files, inspecting a corpus, retrieving contexts, or generating content grounded in a RAG corpus. Do not use for standard database queries (use SQL/Spanner skills), Google…
agent-platform-model-registry
Agent Platform Model Registry Management. Use when you need to upload, list, describe, update, or delete machine learning models (and their versions) in the Agent Platform Model Registry. Don't use for model training, model deployment to endpoints, or managing non-Agent Platform models.
twitter-reader
Read Twitter/X for financial research using opencli (read-only). Use this skill whenever the user wants to read their Twitter feed, search for financial tweets, view bookmarks, look up user profiles, or gather market sentiment from Twitter/X. Triggers include: "check my feed", "search Twitter for", "show my…
chenhao-limit-up
Use when evaluating A-share limit-up (涨停板) setups through Chen Hao's sentiment and momentum lens: market emotion cycles, board strength, follow-through, and short-term aggressive momentum trading.
comet-github
将 Comet GitHub 维护请求路由到基于证据的 PR 审阅、Issue 分诊、本地想法收集、CI 诊断或 Issue 实施流程。用户提到 Comet GitHub Issue/PR 但未指定流程，或询问下一步如何处理时使用。.